基于GAWOA优化ELM的风机变流器故障诊断Fault Diagnosis of Wind Turbine Converter Based on GAWOA-ELM
许如远,马萍
摘要(Abstract)：
为提高双馈异步风力发电机变流器的开路故障诊断准确率，提出一种基于全局自适应鲸鱼优化算法优化极限学习机的故障诊断方法．首先，建立双馈异步风力发电机（DFIG）并网模型，采集网侧变流器故障状态下的三相线电压信号．其次，对采集的电压信号进行快速傅里叶变换，再将三相线电压的不同谐波分量的频率幅值和直流分量重构成特征向量，为去除部分冗余特征，利用邻域保持投影对特征向量进行降维．最后，利用全局自适应鲸鱼算法优化的极限学习机（GAWOA-ELM）对变流器故障进行诊断．使用不同方法对不同信噪比下的变流器故障进行诊断分析，验证了本文所提方法的有效性和鲁棒性．
关键词(KeyWords)： 双馈感应电机;变流器;故障诊断;全局自适应鲸鱼算法;极限学习机
基金项目(Foundation): 国家自然科学基金（52065064;51967019）;; 天山雪松计划（2020XS03）;; 天山青年计划（2020Q066）
作者(Author): 许如远,马萍
DOI: 10.13568/j.cnki.651094.651316.2021.07.08.0001
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